The prediction of three-dimensional protein/ligand conformations and binding free-energies is needed for structure-based drug design. It is believed that these conformations can be calculated by global minimization and analysis of conformational energy functions, but application to practical problems has been difficult because of the multiple-minima problem. Monte Carlo and simulated annealing methods have been successful with small test problems, but have not been applied to realistic problems because of their high-dimensionality and complexity. We are developing a new type of free-energy global minimization method based on renormalization group ideas in which the protein conformation space is dissected into metatable state regions using a temperature- and space-dependent coarse-graining. This provides a novel hierarchical dissection of the underlying structure of the conformation space that we intend to use to guide parallel computational search strategies efficiently along kinetic trajectories similar to those followed by physical proteins.